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首页> 外文期刊>Journal of Intelligence >Predicting Fluid Intelligence by Components of Reaction Time Distributions from Simple Choice Reaction Time Tasks
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Predicting Fluid Intelligence by Components of Reaction Time Distributions from Simple Choice Reaction Time Tasks

机译:通过简单选择反应时间任务,通过反应时间分布的成分预测流体智能

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摘要

Mean reaction times (RT) and the intra-subject variability of RT in simple RT tasks have been shown to predict higher-order cognitive abilities measured with psychometric intelligence tests. To further explore this relationship and to examine its generalizability to a sub-adult-aged sample, we administered different choice RT tasks and Cattell’s Culture Fair Intelligence Test (CFT 20-R) to n = 362 participants aged eight to 18 years. The parameters derived from applying Ratcliff’s diffusion model and an ex-Gaussian model to age-residualized RT data were used to predict fluid intelligence using structural equation models. The drift rate parameter of the diffusion model, as well as σ of the ex-Gaussian model, showed substantial predictive validity regarding fluid intelligence. Our findings demonstrate that stability of performance, more than its mere speed, is relevant for fluid intelligence and we challenge the universality of the worst performance rule observed in adult samples.
机译:在简单的RT任务中,平均反应时间(RT)和RT的受试者内部变异性已显示出可预测通过心理智能测验测得的高阶认知能力。为了进一步探讨这种关系并检验其对亚成人样本的适用性,我们对362名年龄在8至18岁之间的362名参与者进行了不同选择的RT任务和Cattell的文化公平智力测验(CFT 20-R)。通过将Ratcliff扩散模型和前高斯模型应用于年龄残差的RT数据得出的参数用于使用结构方程模型预测流体智能。扩散模型的漂移率参数以及前高斯模型的σ在流体智能方面显示出可观的预测有效性。我们的发现表明,性能稳定性(不仅仅是速度)与流体智能有关,并且我们挑战在成人样本中观察到的最差性能规则的普遍性。

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